Product Management interview question [Product Design]: Design a product for podcast recommendations

Let’s begin this podcast!

In the previous blog, I explained a general framework to solve product management interview questions of sort “Design [X] for [Y]”. Now, I’ll give an example for the same.

This question was posted on www[dot]productmanagementexercises[dot]com and I’m taking this example to explain the framework we learned in the previous blog.

Step 1: Clarify scope -

• What kind of product are we trying to build?
• Is it like a newsletter that goes daily/weekly to subscribed users with top 10 recommendations?
• Is it like a Twitter bot that tweets the links for these podcasts?
• Is it an app or a website or some plugin that plugs to Spotify/ Apple Music/ Google Podcast chrome extension or something? If it’s an app what kind of devices are we targeting?
• Will this make popular recommendations or personalized recommendations?

Going ahead with the assumption that this product is an app for iOS users to make personalized top 10 podcasts recommendations for them based on their interests.

Step 2: Goals -

So as per the assumptions, the goal here is to create an iOS app to make personalized podcast recommendations according to users’ interests.

Step 3: User -

This application is useful for users of any age. Let me explain this -

Kids — Kids probably don’t have the expertise or the resources to find the right podcasts for them. There are very few lists that curate these materials that are ideal for kids. They need some application that tells them what is appropriate and educational for them.

Millennials — Millennials don’t have time to search and listen to every podcast to choose great ones in this fast-paced life, with their colleges to jobs they are occupied with. They want a ready-to-go solution to just open an app and listen to recommended ones.

Adults — Adults have jobs, and families to take care of. Some of them are parents. They don’t have time to go through every podcast and choose the right ones for them. They just want to start listening, that’s it!

User Journey -

The user logs into the app. If they are a first-time user then they need to sign up, using their email id/ phone number. They can one-click sign up using their Facebook/ Gmail.

If the user is not a first-time user they can simply log in using their email/ Gmail/ Facebook.

Once the user is logged in, if they are a first-time user they are asked for their favorite genres, to connect their contacts, Facebook, Spotify, etc to recommend them accordingly.

Step 4: Assumptions -

The assumptions here are that the users are well versed with technology (at least enough to use apps) and they do understand their genres and are able to select their preferred genres.

Another assumption is that they have friends who share similar kinds of traits.

Step 5: Pain Points -

1. Not having time to listen to every podcast and select to listen in the future.
2. Not knowing where to find these podcasts or which service to use to get these recommendations.
3. Parents worry about their kids listening to podcasts that are inappropriate for them.
4. Not knowing what’s trending or what other people are listening to, especially friends and family.
5. Sharing your recommendation as playlists/albums.
6. When learning a new language, one doesn’t know about good creators in that particular language, so recommendations are important.

Prioritization — Usually the pain points are prioritized, but since this is already a niche product and has a limited number of features, we can implement these. Had it been asked to design a product for podcasts or a general recommender system, we could have prioritized these pain points as to what to solve.

Step 6: Solutions -

1. Let users connect their Spotify/Apple Music/Google Podcast accounts to pull their most listened to artists/ genres and make recommendations accordingly.
2. When signing up with the app ask users to select up to 5 genres to get podcast recommendations from.
3. If the user doesn’t know their preferred genres, artists then show them the top 10 podcasts globally/ locally, and similar podcasts to what they already listen to by pulling their podcast app data (reference point 1).
4. Let users add languages of their choice. Users trying to learn another language won’t know who great artists in other languages are.
5. Let users connect their socials (Facebook, Contacts, Twitter, etc) to recommend podcasts from their mutuals.
6. Let them select what mutuals to get recommendations from (while connecting socials all data gets pulled in which means if you have saved a cab driver’s number back from 2013, the recommendations can be made from that, which makes no sense at all so let them select).
7. To share/recommend podcasts to friends on the platform by giving a nudge like “your friend [x] has recommended [y] to you.”
8. A module that contains all the trending podcasts, genre-wise trending podcasts, and global top 10, if in case the users want to explore podcasts outside their favorite genres.
9. Parental control for the accounts of users who are less than 18 years of age allows parents to restrict the recommendation made to just the ones that are educational and appropriate.
10. Optional anonymous profile option (private profile) for users less than 18 years of age.
11. Ability to curate the recommendations in a bundle and share with friends on Facebook, Twitter, etc.
12. Ability to add a recommendation to favorites so that the recommendation algorithm learns more and provides better recommendations over time.

Prioritization — I’ll prioritize these features according to their Impact and Complexity and assign priorities for the same -

feature prioritization according to Impact/Complexity

The features have been prioritized according to their impact and their complexities. The p0 features are a must to have this app working in the right manner, p1, and p2 features can be added later to make the app more useful and provide more control to the users.

Step 7: Success Metrics -

Success metrics for this app can be something like DAU/ MAU to understand whether users are using this app or not.

Another metric can be something like that users listen to at least 20% of the recommendations made by the app.

Step 8: Summary -

We have to design a podcast recommendation app. We analyzed the ideal user group for the product, understood their pain points, the potential solutions for these pain points, prioritized these pain points according to their impact and complexity, and defined metrics to measure its success.

Other optional steps:

Trade-offs: Mention any trade-offs taken into account to implement solutions

Go-to-market: Mention the strategy for launching the product, acquiring customers, etc.

You can check out my answers to this question and other Product Management interview questions here. I’ll be posting more blogs related to product management regularly so stay tuned ;) All the best for your product journey!